GridGain Resources for Architects

Access Our Library of In-Memory Computing Resources

GridGain produces a wide selection of resources that can help you understand how our in-memory computing platform can fit within your existing or new architectures. Whether your organization needs to speed up and scale out an existing application or you are focused on the development of a new, modern application architecture, our resources can help you understand how GridGain can help. Select from our extensive library of white papers, webinars, case studies, application notes, ebook and more.

Resources

Modernizing Capital Markets Applications with In-Memory Computing

Capital markets applications often require high performance, massive scalability, and high-performance data access across the enterprise to meet the demands of modern, digital business activities. In addition, digital transformations may require capital markets companies to design architectures that enable multiple business applications to access data from multiple, disparate data sources in real time.

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Options for Adding Speed and Scale to MySQL
This white paper provides insight on improving the scale, speed, and agility of MySQL so that it can support the digital transformation initiatives of today's enterprises. New business needs and performance demands have pushed many applications beyond MySQL's (and other RDBMSs) architectural limits. In many cases, the issues cannot be remedied by just fixing MySQL.
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PostgreSQL Speed and Scale Options with In-Memory Computing
This white paper explains how to use in-memory computing to add PostgreSQL speed and scale options to end-to-end IT infrastructure—both from PostgreSQL-centric vendors and from other open source and third-party products. It also explains how help create flexible IT infrastructure over time to both increase speed and scale.
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A Roadmap for In-Memory Computing: Current and Emerging Use Cases
Learn how high-performance in-memory computing architecture is rapidly becoming the method of choice for today’s real-time applications that are focused on big data, fast data, streaming analytics or machine and deep learning.
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In-Memory Computing Options for SAP Customers: When to Use SAP HANA, or Something Else
Download this white paper to learn about your options for adding speed, scale and agility to end-to-end IT infrastructure—from SAP HANA to third-party vendors and open source. It also explains how to evolve your architecture over time for speed and scale, become more flexible to change, and support new technologies as needed.
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Increasing Microsoft SQL Server Speed and Scale with In-Memory Computing
This white paper discusses how to increase Microsoft® SQL Server® speed and scale using in-memory computing. There are options for adding speed and scale to Microsoft SQL Server® at the database level—including SQL Server Always On Availability Groups and SQL Server In-Memory OLTP—and each has its place. But when the speed and scale needs extend beyond the database layer, the best long term approach is in-memory computing.
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Using In-Memory Computing to Add Speed and Scale to Oracle
This white paper discusses how to increase and accelerate your Oracle database speed and scale using in-memory computing. There are many Oracle® options for adding speed and scale to Oracle Database, or for replacing it—including Oracle RAC, Oracle Database In-Memory, Oracle Exadata, Oracle GoldenGate, Oracle TimesTen Classic, Oracle TimesTen Scaleout, and Oracle Coherence—and each has its place. But when the speed and scale really needs to be addressed beyond database layer, the best long-term approach is in-memory computing. This white paper discusses in-memory computing options for your Oracle database deployment.
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GridGain vs Redis: The Advantages of In-Memory Computing Over Caching
This white paper will take a detailed look at the challenges faced by companies that have either used Redis and run into its limitations, or are considering Redis and find it is insufficient for their needs. This paper will also discuss how the GridGain in-memory computing platform has helped companies overcome the limitations of Redis for existing and new applications, and how GridGain has helped improve the customer experience.
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Empowering Insurance Companies with In-Memory Computing
This white paper discusses the challenges facing today’s insurance industry, the opportunities new technologies can offer, and the crucial edge that providers can gain with solutions such as the GridGain in-memory computing platform.
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Boost Performance of Financial Services IOT Projects with In-Memory Computing
This white paper discusses how an in-memory computing platform solution like GridGain gives financial services companies the speed, scalability, and flexibility they need to build successful IoT-based applications and services.
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Troubleshooting Apache® Ignite™

Вебинар прошел, но вы можете получить доступ к видео и слайдам, заполнив форму справа.

Команда Customer Solutions GridGain ежедневно решает задачи, связанные с развертыванием и эксплуатацией In-memory платформы. На вебинаре инженер этой команды Станислав Лукьянов поделится наработками как: 

Apache® Ignite™ for Node.js Developers
This webinar will give you a solid understanding of how to use Node.js with Apache Ignite. Attendees can then use this knowledge to build scalable Node.js applications with Ignite.
Troubleshooting Apache Ignite
Learn the best practices that the GridGain® Customer Solutions team has used to troubleshoot hundreds of Apache® Ignite™ deployments. We will share with you how to set up deployments to make them easier to monitor, manage and keep up and running properly.
Troubleshooting Apache® Ignite™

Whether you are getting started with Apache Ignite or already deployed, this session is for you. Learn the best practices that the GridGain® Customer Solutions team has used to troubleshoot hundreds of deployments. We will share with you how to set up deployments to make them easier to monitor, manage and keep up and running properly. In this session, you will see best practice examples on how to:

EMEA Webinar - What's New in Apache Ignite 2.7

Learn what's new with Apache Ignite 2.7. This session, given by Akmal Chaudhri, GridGain Evangelist for Apache Ignite, is for all Apache Ignite users. You will learn how the new capabilities of Apache Ignite work. You will also understand more about some of the other changes made to Apache Ignite, and the reasoning behind them. Come with your questions, and learn from the questions of your peers. Topics covered include:

Scalable Full Text Search with Apache Ignite

Many modern applications provide full text search as a core feature of the overall product.
There are good open source and commercial options available already, but what if all your data is in Apache Ignite? Do you really need to pull in another system to solve this problem?

The short answer is no. Ignite has built in support for fulltext indexing of content. If you use the SQL APIs there is an off the shelf option which just works and suits many use cases. If you use the key value APIs this is less true.

In-Memory Computing в логистике

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In-Memory Computing Best Practices: Developing New Apps, Channels and APIs

Digital transformation is arguably the most important initiative in IT today, in large part because of its ability to improve the customer experience and business operations, and to make a business more agile. But delivering a responsive digital business is not possible at scale without in-memory computing. This session dives into how in-memory computing acts as a foundation for digital business.  Topics include how in-memory computing is used to:

GridGain Cloud: Deploy Apache Ignite in Minutes
Learn how to deploy Ignite as a service with just a few clicks, and how to use Ignite as a distributed cache or in-memory database (IMDB) as a service. This session is hands-on, showing all the steps you need to take to get up and running, and how to develop, deploy, monitor and manage an Ignite cluster in the cloud.
Использование Apache Ignite в качестве фреймворка для распределенного выполнения задач

Вебинар завершился.  Заполните форму, чтобы получить доступ к видео и слайдам. 

Apache Ignite применяется в самых разных системах: банки, логистика, e-commerce… а некоторые кейсы похожи на научную фантастику. Например, этот биотех-проект из Новосибирска. Присоединяйтесь онлайн, чтобы узнать больше.

Expedia Case Study

Using Apache Ignite after moving from an Apache® Cassandra™ caching architecture, Expedia reduced query times from 3 seconds to 150 milliseconds for millions of daily searches ― a 95% improvement. By accelerating the speed of flight data queries, Expedia contributes significantly to high levels of customer satisfaction, customer retention, and competitive differentiation.

FSB Technology Case Study

FSB deployed GridGain to speed up its Postgres database and scale-out their cluster. For FSB Technology to support live betting during sporting events, their betting platform must be real-time and highly performant. Huge amounts of event data must be constantly updated, and immediately available to a vast number of clients. GridGain Enterprise Edition helped FSB add nodes in the Rackspace public cloud during especially busy weekends with major sporting events.

Finastra Case Study

Finastra deployed the GridGain in-memory computing platform to embrace real-time services and satisfy evolving compliance, reporting regulations, and customer demands in Europe. As a large financial technology company, Finastra solutions must manage huge amounts of trade and accounting data. Finastra used GridGain to help to implement a new Java-based IT stack that supports data lakes instead of traditional databases.

e-Therapeutics Case Study

The GridGain In-Memory Computing Platform powers e-Therapeutics’ Network Pharmacology platform so that they can identify and analyze specific networks of proteins associated with a particular disease based on computational analysis of disease cells. While performing a single analysis is relatively straightforward and does not take a lot of time, the e-Therapeutics approach involves hundreds of thousands of analyses across multiple parameter sets and assumptions, resulting in an extraordinarily compute-intensive environment.

Cyber Dust Case Study

Cyber Dust uses the GridGain in-memory computing platform to power its messaging platform. Cyber Dust delivers millions of texts a day. GridGain helps Cyber Dust process messages quickly enough in real-time and enables the company to avoid writing messages onto the database, allowing it to completely wipe clean every text and not leave a forensically recoverable trace of any message sent over its service.

International Bank Case Study

International Bank Counts on HPC and Fast Data with GridGain® A leading international bank offering investment advisory and wealth management services to private and institutional clients around the world was looking to upgrade its custom-built software system to a High Performance Computing (HPC) solution.

Experticity Case Study

Expertcity uses GridGain in-memory computing solutions to power its platform that allows over 650 lifestyle and consumer brands to connect with key brand advocates to help them improve sales in their retail channels. Experticity uses GridGain so that its architecture scales with company growth, analyzes the data quickly enough to send users to the next logical step in the personalized process, and delivers analytics information accurately and in real-time to the ever-changing data collection.

MercuryGate Case Study

Mercury Gate uses the GridGain in-memory computing platform to power its global Transportation Management Systems (TMS) for shippers, carriers, brokers, freight forwarders and third-party logistics providers. GridGain helps MercuryGate meet customer performance expectations: clients require rate information on their many shipping needs first thing in the morning and they need it quickly in order to make smart decisions that keep them competitive, save money and increase profits.

Intelligentpipe Case Study

Intelligentpipe Leverages GridGain® In-Memory Computing Platform for Real-Time Analytics Big Data Software Company Leverages GridGain for Terabytes of Mobile User Traffic Data With offices in Finland and Singapore, Intelligentpipe is a big data software company serving the global telecommunications industry by developing solutions for mobile operators to improve their business and operational processes.

Case Study: ChronoTrack

ChronoTrack selected GridGain in-memory computing solutions to help process the data from races: times, ranks and scores tens of thousands of participants in hundreds of races every week. The ChronoTrack system captures participant data multiple times in a single race across several categories. With that data, they use a calculation algorithm to establish rankings quickly. They needed a high-performance solution that distributes the algorithm calculation jobs for each race participant across many servers so race results would be available in real-time.
GridGain Managed Services: GridGain Nebula

GridGain offers highly responsive, reliable managed services – known as GridGain Nebula – for the Apache Ignite or GridGain in-memory computing platforms at a fraction of the cost of staffing an internal team. We can manage your environment 24x7, whether on-premises, on a private or public cloud, or on a hybrid environment. Download the datasheet to learn more.

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GridGain Basic Support for Apache Ignite and GridGain Community Edition

If your company is one of the tens of thousands of organizations that use Apache® IgniteTM or GridGain® Community Edition in a production environment, GridGain Basic Support can provide you with peace of mind that you have a trusted partner to help keep your environment running flawlessly. The service includes....

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GridGain In-Memory Computing Platform
This data sheet provides the key features and benefits of the GridGain in-memory computing platform.
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GridGain In-Memory Accelerator for Hadoop and Spark
This data sheet provides the key features and benefits of the GridGain In-Memory Accelerator for Hadoop and Spark.
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